Aggregate blending via robust linear programming

Aggregate blending is a problem frequently encountered in the construction industry. In this article, it is shown that robust linear programming can be used to produce solutions protected against noisy data with the same computational complexity of the classic optimization methods for the problem. It is also shown that nonlinear cost functions can be approximated by piecewise linear functions, keeping complexity at a low level. Finally, experimental results are presented. The aim is to understand how robust linear programming solutions compare with those of other methods previously described in the literature and to evaluate the actual quality of the robust solutions.